def compile_tree(node,
tree_state,
sdd_state,
label="0",
st=None,
path_sdd=None):
if st is None: st = ""
mgr = sdd_state.manager
if path_sdd is None:
path_sdd = sdd.sdd_manager_true(mgr)
tree = tree_state.tree
children = tree.successors(node)
if len(children) == 0:
node_label = node.attr['label']
node_label = node_label.split(':')[-1].strip().split(' ')[0]
if label == node_label:
# disjoin path
#print st
alpha = sdd.sdd_disjoin(sdd_state.alpha, path_sdd, mgr)
sdd.sdd_deref(sdd_state.alpha, mgr)
sdd.sdd_ref(alpha, mgr)
sdd_state.alpha = alpha
else:
for child in children:
edge = tree.get_edge(node, child)
var = node.attr['label'].split(' ')[-1]
val = edge.attr['label'].split(' ')[-1]
child_st = st + "%s:%s " % (var, val)
# extend path
base_var = "_".join(var.split('_')[:-1]) + "_%d"
cur_index = int(var.split('_')[-1])
low_index, high_index = 0, tree_state.constraint_info[base_var][0]
beta = sdd.sdd_manager_false(mgr)
if val == ">=":
for i in xrange(cur_index + 1, high_index):
sdd_lit = tree_state.domain[base_var % i]
beta = sdd.sdd_disjoin(
beta, sdd.sdd_manager_literal(sdd_lit, mgr), mgr)
else: # val == "<"
for i in xrange(low_index, cur_index + 1):
sdd_lit = tree_state.domain[base_var % i]
beta = sdd.sdd_disjoin(
beta, sdd.sdd_manager_literal(sdd_lit, mgr), mgr)
sdd_var = tree_state.domain[var]
new_path_sdd = sdd.sdd_conjoin(path_sdd, beta, mgr)
sdd_state.used_vars.add(sdd_var)
child_st = st + "%s:%s " % (var, val)
sdd.sdd_ref(new_path_sdd, mgr)
compile_tree(child,
tree_state,
sdd_state,
label=label,
st=child_st,
path_sdd=new_path_sdd)
sdd.sdd_deref(new_path_sdd, mgr)
def _primes_two(alpha, variables, cache1, cache2, pmgr, mgr):
if len(variables) == 0:
if sdd.sdd_node_is_false(alpha): return sdd.sdd_manager_false(pmgr)
if sdd.sdd_node_is_true(alpha): return sdd.sdd_manager_true(pmgr)
key = (len(variables), sdd.sdd_id(alpha))
if key in cache1:
global cache_hits
cache_hits += 1
if cache_hits % 1000 == 0: print "cache-hits-update:", cache_hits
return cache1[key]
var, remaining = variables[0], variables[1:]
alpha0 = sdd.sdd_condition(-var, alpha, mgr)
alpha1 = sdd.sdd_condition(var, alpha, mgr)
primes0 = _primes_two(alpha0, remaining, cache1, cache2, pmgr, mgr)
primes1 = _primes_two(alpha1, remaining, cache1, cache2, pmgr, mgr)
qrimes0 = _keep_imp(primes0, alpha1, remaining, cache1, cache2, pmgr, mgr)
qrimes1 = _keep_imp(primes1, alpha0, remaining, cache1, cache2, pmgr, mgr)
gamma = sdd.sdd_disjoin(qrimes0, qrimes1, pmgr)
gamma = sdd.sdd_conjoin(_sdd_unused(var, pmgr), gamma, pmgr)
kappa = sdd.sdd_conjoin(primes0, sdd.sdd_negate(qrimes0, pmgr), pmgr)
kappa = sdd.sdd_conjoin(kappa, _sdd_used_neg(var, pmgr), pmgr)
gamma = sdd.sdd_disjoin(gamma, kappa, pmgr)
kappa = sdd.sdd_conjoin(primes1, sdd.sdd_negate(qrimes1, pmgr), pmgr)
kappa = sdd.sdd_conjoin(kappa, _sdd_used_pos(var, pmgr), pmgr)
gamma = sdd.sdd_disjoin(gamma, kappa, pmgr)
cache1[key] = gamma
return gamma
def _primes_one_given_term(alpha, variables, inst, cache, cache_dummy, pmgr,
mgr):
if len(variables) == 0:
if sdd.sdd_node_is_true(alpha): return sdd.sdd_manager_true(pmgr)
if sdd.sdd_node_is_false(alpha): return sdd.sdd_manager_false(pmgr)
#add cases for true/false
key = (len(variables), sdd.sdd_id(alpha))
if key in cache:
return cache[key]
var, remaining = variables[0], variables[1:]
val, remaining_val = inst[0], inst[1:]
beta2 = sdd.sdd_forall(var, alpha, mgr)
gamma2 = _primes_one_given_term(beta2, remaining, remaining_val, cache,
cache_dummy, pmgr, mgr)
gamma9 = gamma2
pvar = 3 * (var - 1) + 1
kappa2 = sdd.sdd_manager_literal(-pvar, pmgr)
gamma2 = sdd.sdd_conjoin(gamma2, kappa2, pmgr)
if val == 0:
beta0 = sdd.sdd_condition(-var, alpha, mgr)
gamma0 = _primes_one_given_term(beta0, remaining, remaining_val, cache,
cache_dummy, pmgr, mgr)
gamma0 = sdd.sdd_conjoin(gamma0, sdd.sdd_negate(gamma9, pmgr), pmgr)
kappa0 = sdd.sdd_conjoin(sdd.sdd_manager_literal(-(pvar + 1), pmgr),
sdd.sdd_manager_literal((pvar + 2), pmgr),
pmgr)
kappa0 = sdd.sdd_conjoin(kappa0, sdd.sdd_manager_literal(pvar, pmgr),
pmgr)
gamma0 = sdd.sdd_conjoin(gamma0, kappa0, pmgr)
#gamma0 = sdd.sdd_conjoin(gamma0,sdd.sdd_negate(gamma9,pmgr),pmgr)
if val == 1:
beta1 = sdd.sdd_condition(var, alpha, mgr)
gamma1 = _primes_one_given_term(beta1, remaining, remaining_val, cache,
cache_dummy, pmgr, mgr)
gamma1 = sdd.sdd_conjoin(gamma1, sdd.sdd_negate(gamma9, pmgr), pmgr)
kappa1 = sdd.sdd_conjoin(sdd.sdd_manager_literal((pvar + 1), pmgr),
sdd.sdd_manager_literal(-(pvar + 2), pmgr),
pmgr)
kappa1 = sdd.sdd_conjoin(kappa1, sdd.sdd_manager_literal(pvar, pmgr),
pmgr)
gamma1 = sdd.sdd_conjoin(gamma1, kappa1, pmgr)
#gamma1 = sdd.sdd_conjoin(gamma1,sdd.sdd_negate(gamma9,pmgr),pmgr)
if val == 0:
gamma = sdd.sdd_disjoin(gamma0, gamma2, pmgr)
if val == 1:
gamma = sdd.sdd_disjoin(gamma1, gamma2, pmgr)
#gamma = sdd.sdd_disjoin(sdd.sdd_disjoin(gamma0, gamma1, pmgr), gamma2, pmgr)
#if len(variables) > 60:
# print len(variables), sdd.sdd_manager_count(mgr)
cache[key] = gamma
return gamma
def test_admission():
var_count = 4
vtree = sdd.sdd_vtree_new(var_count, "balanced")
mgr = sdd.sdd_manager_new(vtree)
# WFEG
# ( w ^ g )
alpha = sdd.sdd_conjoin(sdd.sdd_manager_literal(1, mgr),
sdd.sdd_manager_literal(4, mgr), mgr)
# ( w ^ f ^ e )
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(1, mgr),
sdd.sdd_manager_literal(2, mgr), mgr)
beta = sdd.sdd_conjoin(beta, sdd.sdd_manager_literal(3, mgr), mgr)
# ( f ^ e ^ g )
gamma = sdd.sdd_conjoin(sdd.sdd_manager_literal(2, mgr),
sdd.sdd_manager_literal(3, mgr), mgr)
gamma = sdd.sdd_conjoin(gamma, sdd.sdd_manager_literal(4, mgr), mgr)
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
alpha = sdd.sdd_disjoin(alpha, gamma, mgr)
alpha = sdd.sdd_negate(alpha, mgr)
beta, pmgr = primes(alpha, mgr)
_sanity_check(alpha, mgr, beta, pmgr)
vtree = sdd.sdd_manager_vtree(mgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
import models
for model in models.models(alpha, vtree):
print models.str_model(model)
for model in models.models(beta, pvtree):
print models.str_model(model)
for model in models.models(alpha, vtree):
print "==", models.str_model(model)
model_list = [model[var] for var in sorted(model.keys())]
gamma, pmgr = compatible_primes(alpha,
model_list,
mgr,
primes_mgr=(beta, pmgr))
pvtree = sdd.sdd_manager_vtree(pmgr)
for prime_model in models.models(gamma, pvtree):
print models.str_model(prime_model)
term = prime_to_dict(prime_model, var_count)
print " ".join([
("*" if var not in term else "+" if term[var] == 1 else "-")
for var in xrange(1, var_count + 1)
])
print "dead-nodes:", sdd.sdd_manager_dead_count(mgr)
print "dead-nodes:", sdd.sdd_manager_dead_count(pmgr)
def parse_bdd(filename):
var_count,node_count = pre_parse_bdd(filename)
print " zdd var count:", var_count
print " zdd node count:", node_count
manager = start_manager(var_count,range(1,var_count+1))
root = sdd.sdd_manager_vtree(manager)
nodes = [None] * (node_count+1)
index,id2index = 1,{}
f = open(filename)
for line in f.readlines():
if line.startswith("."): break
line = line.strip().split()
nid = int(line[0])
dvar = int(line[1])
lo,hi = line[2],line[3]
hi_lit = sdd.sdd_manager_literal( dvar,manager)
lo_lit = sdd.sdd_manager_literal(-dvar,manager)
if lo == 'T':
lo_sdd,lo_vtree = sdd.sdd_manager_true(manager),None
elif lo == 'B':
lo_sdd,lo_vtree = sdd.sdd_manager_false(manager),None
else:
lo_id = int(lo)
lo_sdd,lo_vtree = nodes[id2index[lo_id]]
if hi == 'T':
hi_sdd,hi_vtree = sdd.sdd_manager_true(manager),None
elif hi == 'B':
hi_sdd,hi_vtree = sdd.sdd_manager_false(manager),None
else:
hi_id = int(hi)
hi_sdd,hi_vtree = nodes[id2index[hi_id]]
#v1,v2 = sdd.sdd_vtree_of(hi_lit),sdd.sdd_vtree_of(hi_sdd)
#vt = sdd.sdd_vtree_lca(v1,v2,root)
vt = sdd.sdd_manager_vtree_of_var(dvar,manager)
vt = sdd.sdd_vtree_parent(vt)
vt = sdd.sdd_vtree_right(vt)
if dvar < var_count:
hi_sdd = zero_normalize_sdd(hi_sdd,hi_vtree,vt,manager)
lo_sdd = zero_normalize_sdd(lo_sdd,lo_vtree,vt,manager)
vt = sdd.sdd_vtree_parent(vt)
hi_sdd = sdd.sdd_conjoin(hi_lit,hi_sdd,manager)
lo_sdd = sdd.sdd_conjoin(lo_lit,lo_sdd,manager)
alpha = sdd.sdd_disjoin(hi_sdd,lo_sdd,manager)
nodes[index] = (alpha,vt)
id2index[nid] = index
index += 1
f.close()
return manager,nodes[-1][0]
def GetLocalConstraintsForRoot(self, file_prefix):
then_vtree_filename = "%s/%s_then_vtree.vtree" % (file_prefix,
self.name)
then_sdd_filename = "%s/%s_then_sdd.sdd" % (file_prefix, self.name)
constraint = {}
constraint["then_vtree"] = then_vtree_filename
constraint["then"] = [then_sdd_filename]
universe = []
# internal edges
for sub_region_edge_tup in self.sub_region_edges:
universe.append(sub_region_edge_tup)
GraphSet.set_universe(universe)
universe = GraphSet.universe()
paths = GraphSet()
child_names = self.children.keys()
for (i, j) in itertools.combinations(child_names, 2):
paths = paths.union(GraphSet.paths(i, j))
name_to_sdd_index = {}
zdd_to_sdd_index = [None] # for generating sdd from graphset
sdd_index = 0
for child in child_names:
sdd_index += 1
name_to_sdd_index["c%s" % child] = sdd_index
for sub_region_edge in universe:
corresponding_network_edges = self.sub_region_edges[
sub_region_edge]
coresponding_network_edges_sdd_index = []
for single_edge in corresponding_network_edges:
sdd_index += 1
name_to_sdd_index[str(single_edge)] = sdd_index
coresponding_network_edges_sdd_index.append(sdd_index)
zdd_to_sdd_index.append(coresponding_network_edges_sdd_index)
constraint["then_variable_mapping"] = name_to_sdd_index
rl_vtree = sdd.sdd_vtree_new(sdd_index, "right")
sdd_manager = sdd.sdd_manager_new(rl_vtree)
sdd.sdd_vtree_free(rl_vtree)
sdd.sdd_manager_auto_gc_and_minimize_off(sdd_manager)
# Construct simple path constraint
simple_path_constraint = generate_sdd_from_graphset(
paths, sdd_manager, zdd_to_sdd_index)
# non empty path in this region map
none_of_child = sdd.util.sdd_negative_term(
sdd_manager,
[name_to_sdd_index["c%s" % child] for child in self.children])
case_one = sdd.sdd_conjoin(none_of_child, simple_path_constraint,
sdd_manager)
# empty path in this region map
exactly_one_child = sdd.util.sdd_exactly_one(
sdd_manager,
[name_to_sdd_index["c%s" % child] for child in self.children])
empty_path_constraint = sdd.util.sdd_negative_term(
sdd_manager, sum(zdd_to_sdd_index[1:], []))
case_two = sdd.sdd_conjoin(exactly_one_child, empty_path_constraint,
sdd_manager)
total_constraint = sdd.sdd_disjoin(case_one, case_two, sdd_manager)
sdd.sdd_save(then_sdd_filename, total_constraint)
sdd.sdd_vtree_save(then_vtree_filename,
sdd.sdd_manager_vtree(sdd_manager))
sdd.sdd_manager_free(sdd_manager)
return constraint
def test():
var_count = 4
vtree = sdd.sdd_vtree_new(var_count, "balanced")
mgr = sdd.sdd_manager_new(vtree)
# A v B
alpha = sdd.sdd_disjoin(sdd.sdd_manager_literal(1, mgr),
sdd.sdd_manager_literal(2, mgr), mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(-3, mgr),
sdd.sdd_manager_literal(-4, mgr), mgr)
# A v B v ( ~C ^ ~D )
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
beta, pmgr = primes(alpha, mgr)
_sanity_check(alpha, mgr, beta, pmgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
import models
#beta2 = sdd.sdd_global_minimize_cardinality(beta,pmgr)
beta2 = beta
for model in models.models(beta2, pvtree):
print models.str_model(model)
global cache_hits
print "cache-hits:", cache_hits
print "all-ones"
beta, pmgr = compatible_primes(alpha, [1, 1, 1, 1], mgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
for model in models.models(beta, pvtree):
print models.str_model(model)
print "all-zeros"
beta, pmgr = compatible_primes(alpha, [0, 0, 0, 0], mgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
for model in models.models(beta, pvtree):
print models.str_model(model)
print "blah"
beta, pmgr = compatible_primes(alpha, [1, 0, 1, 0], mgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
for model in models.models(beta, pvtree):
print models.str_model(model)
print "dead-nodes:", sdd.sdd_manager_dead_count(mgr)
print "dead-nodes:", sdd.sdd_manager_dead_count(pmgr)
def _remove_dummies(alpha, var_count, pmgr):
for var in xrange(1, var_count + 1):
var = 3 * (var - 1) + 1
beta = sdd.sdd_manager_literal(-var, pmgr)
gamma = sdd.sdd_disjoin(sdd.sdd_manager_literal(var + 1, pmgr),
sdd.sdd_manager_literal(var + 2, pmgr), pmgr)
beta = sdd.sdd_conjoin(beta, gamma, pmgr)
alpha = sdd.sdd_conjoin(alpha, sdd.sdd_negate(beta, pmgr), pmgr)
return alpha
def encode_unique_constraint(values, mgr):
alpha = sdd.sdd_manager_true(mgr)
# at most one
for v1 in values:
for v2 in values:
if v1 == v2: continue
beta = sdd.sdd_disjoin(sdd.sdd_manager_literal(-1 * v1, mgr),
sdd.sdd_manager_literal(-1 * v2, mgr), mgr)
alpha = sdd.sdd_conjoin(alpha, beta, mgr)
# at least one
beta = sdd.sdd_manager_false(mgr)
for v in values:
beta = sdd.sdd_disjoin(beta, sdd.sdd_manager_literal(v, mgr), mgr)
alpha = sdd.sdd_conjoin(alpha, beta, mgr)
return alpha
def _primes_one(alpha, variables, cache, cache_dummy, pmgr, mgr):
if len(variables) == 0:
if sdd.sdd_node_is_true(alpha): return sdd.sdd_manager_true(pmgr)
if sdd.sdd_node_is_false(alpha): return sdd.sdd_manager_false(pmgr)
#add cases for true/false
key = (len(variables), sdd.sdd_id(alpha))
if key in cache:
global cache_hits
cache_hits += 1
#if cache_hits % 1000 == 0: print "cache-hits-update:", cache_hits
return cache[key]
var, remaining = variables[0], variables[1:]
beta2 = sdd.sdd_forall(var, alpha, mgr)
gamma2 = _primes_one(beta2, remaining, cache, cache_dummy, pmgr, mgr)
gamma9 = gamma2
pvar = 3 * (var - 1) + 1
kappa2 = sdd.sdd_manager_literal(-pvar, pmgr)
gamma2 = sdd.sdd_conjoin(gamma2, kappa2, pmgr)
beta0 = sdd.sdd_condition(-var, alpha, mgr)
gamma0 = _primes_one(beta0, remaining, cache, cache_dummy, pmgr, mgr)
gamma0 = sdd.sdd_conjoin(gamma0, sdd.sdd_negate(gamma9, pmgr), pmgr)
kappa0 = sdd.sdd_conjoin(sdd.sdd_manager_literal(-(pvar + 1), pmgr),
sdd.sdd_manager_literal((pvar + 2), pmgr), pmgr)
kappa0 = sdd.sdd_conjoin(kappa0, sdd.sdd_manager_literal(pvar, pmgr), pmgr)
gamma0 = sdd.sdd_conjoin(gamma0, kappa0, pmgr)
#gamma0 = sdd.sdd_conjoin(gamma0,sdd.sdd_negate(gamma9,pmgr),pmgr)
beta1 = sdd.sdd_condition(var, alpha, mgr)
gamma1 = _primes_one(beta1, remaining, cache, cache_dummy, pmgr, mgr)
gamma1 = sdd.sdd_conjoin(gamma1, sdd.sdd_negate(gamma9, pmgr), pmgr)
kappa1 = sdd.sdd_conjoin(sdd.sdd_manager_literal((pvar + 1), pmgr),
sdd.sdd_manager_literal(-(pvar + 2), pmgr), pmgr)
kappa1 = sdd.sdd_conjoin(kappa1, sdd.sdd_manager_literal(pvar, pmgr), pmgr)
gamma1 = sdd.sdd_conjoin(gamma1, kappa1, pmgr)
#gamma1 = sdd.sdd_conjoin(gamma1,sdd.sdd_negate(gamma9,pmgr),pmgr)
gamma = sdd.sdd_disjoin(gamma0, gamma1, pmgr)
gamma = sdd.sdd_disjoin(gamma, gamma2, pmgr)
cache[key] = gamma
return gamma
def test_andy():
var_count = 3
vtree = sdd.sdd_vtree_new(var_count, "balanced")
mgr = sdd.sdd_manager_new(vtree)
# 100, 101, 111, 001, 011
alpha = sdd.sdd_manager_false(mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(1, mgr),
sdd.sdd_manager_literal(-2, mgr), mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(-3, mgr), beta, mgr)
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(1, mgr),
sdd.sdd_manager_literal(-2, mgr), mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(3, mgr), beta, mgr)
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(1, mgr),
sdd.sdd_manager_literal(2, mgr), mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(3, mgr), beta, mgr)
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(-1, mgr),
sdd.sdd_manager_literal(-2, mgr), mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(3, mgr), beta, mgr)
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(-1, mgr),
sdd.sdd_manager_literal(2, mgr), mgr)
beta = sdd.sdd_conjoin(sdd.sdd_manager_literal(3, mgr), beta, mgr)
alpha = sdd.sdd_disjoin(alpha, beta, mgr)
beta, pmgr = primes(alpha, mgr)
_sanity_check(alpha, mgr, beta, pmgr)
vtree = sdd.sdd_manager_vtree(mgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
import models
for model in models.models(alpha, vtree):
print models.str_model(model)
for model in models.models(beta, pvtree):
print models.str_model(model)
print "dead-nodes:", sdd.sdd_manager_dead_count(mgr)
print "dead-nodes:", sdd.sdd_manager_dead_count(pmgr)
def _keep_imp(beta, alpha, variables, cache1, cache2, pmgr, mgr):
#if len(variables) == 0:
if sdd.sdd_node_is_false(beta): return sdd.sdd_manager_false(pmgr)
if sdd.sdd_node_is_false(alpha): return sdd.sdd_manager_false(pmgr)
if sdd.sdd_node_is_true(alpha): return beta
key = (len(variables), sdd.sdd_id(alpha), sdd.sdd_id(beta))
if key in cache2:
global cache_hits
cache_hits += 1
#if cache_hits % 1000 == 0: print "cache-hits-update:", cache_hits
return cache2[key]
var, remaining = variables[0], variables[1:]
pvar = 3 * (var - 1) + 1
alpha0 = sdd.sdd_condition(-var, alpha, mgr)
alpha1 = sdd.sdd_condition(var, alpha, mgr)
beta0 = sdd.sdd_condition(pvar, beta, pmgr)
beta0 = sdd.sdd_condition(-(pvar + 1), beta0, pmgr)
#beta0 = sdd.sdd_condition( (pvar+2),beta0,pmgr)
beta1 = sdd.sdd_condition(pvar, beta, pmgr)
beta1 = sdd.sdd_condition((pvar + 1), beta1, pmgr)
#beta1 = sdd.sdd_condition(-(pvar+2),beta1,pmgr)
betad = sdd.sdd_condition(-pvar, beta, pmgr)
P = _keep_imp(betad, alpha0, remaining, cache1, cache2, pmgr, mgr)
Q = _keep_imp(betad, alpha1, remaining, cache1, cache2, pmgr, mgr)
R0 = _keep_imp(beta0, alpha0, remaining, cache1, cache2, pmgr, mgr)
R1 = _keep_imp(beta1, alpha1, remaining, cache1, cache2, pmgr, mgr)
gamma = sdd.sdd_conjoin(P, Q, pmgr)
gamma = sdd.sdd_conjoin(_sdd_unused(var, pmgr), gamma, pmgr)
kappa = sdd.sdd_conjoin(_sdd_used_neg(var, pmgr), R0, pmgr)
gamma = sdd.sdd_disjoin(gamma, kappa, pmgr)
kappa = sdd.sdd_conjoin(_sdd_used_pos(var, pmgr), R1, pmgr)
gamma = sdd.sdd_disjoin(gamma, kappa, pmgr)
cache2[key] = gamma
return gamma
def generate_exactly_two_from_tuples(sdd_manager, tuples, variables):
result_constraint = sdd.sdd_manager_false(sdd_manager)
for cur_tup in tuples:
cur_term = sdd.sdd_manager_true(sdd_manager)
for cur_var in variables:
if cur_var in cur_tup:
cur_term = sdd.sdd_conjoin(
cur_term, sdd.sdd_manager_literal(cur_var, sdd_manager),
sdd_manager)
else:
cur_term = sdd.sdd_conjoin(
cur_term, sdd.sdd_manager_literal(-cur_var, sdd_manager),
sdd_manager)
result_constraint = sdd.sdd_disjoin(cur_term, result_constraint,
sdd_manager)
return result_constraint
def _sanity_check(f, mgr, g, pmgr):
"""f is original function and g is its prime implicants"""
alpha = sdd.sdd_manager_false(mgr)
pvtree = sdd.sdd_manager_vtree(pmgr)
for prime in models.models(g, pvtree):
term = prime_to_term(prime, mgr)
beta = sdd.sdd_conjoin(term, f, mgr)
assert term == beta
assert _is_prime(prime, f, mgr)
alpha = sdd.sdd_disjoin(alpha, term, mgr)
mc1 = sdd.sdd_global_model_count(f, mgr)
mc2 = sdd.sdd_global_model_count(alpha, mgr)
print "mc-check:", mc1, mc2, ("ok" if mc1 == mc2 else "NOT OK")
assert mc1 == mc2
assert alpha == f
def compatible_primes(alpha, inst, mgr, primes_mgr=None):
if primes_mgr is None:
beta, pmgr = primes(alpha, mgr)
else:
beta, pmgr = primes_mgr
asdf = beta
for i, val in enumerate(inst):
var = i + 1
pvar = 3 * (var - 1) + 1
lit = (pvar + 1) if val == 1 else -(pvar + 1)
gamma = sdd.sdd_conjoin(sdd.sdd_manager_literal(pvar, pmgr),
sdd.sdd_manager_literal(lit, pmgr), pmgr)
gamma = sdd.sdd_disjoin(gamma, sdd.sdd_manager_literal(-pvar, pmgr),
pmgr)
beta = sdd.sdd_conjoin(beta, gamma, pmgr)
return beta, pmgr
def convert_helper(node, mgr, obdd, dp, depth):
if node == 'S1':
return sdd.sdd_manager_true(mgr)
if node == 'S0':
return sdd.sdd_manager_false(mgr)
if node in dp:
return dp[node]
var, ch0, ch1 = obdd[node][0] + 1, obdd[node][1], obdd[node][2]
#print var
alpha = sdd.sdd_conjoin(convert_helper(ch0, mgr, obdd, dp, depth + 1),
sdd.sdd_manager_literal(-1 * var, mgr), mgr)
beta = sdd.sdd_conjoin(convert_helper(ch1, mgr, obdd, dp, depth + 1),
sdd.sdd_manager_literal(var, mgr), mgr)
dp[node] = sdd.sdd_disjoin(alpha, beta, mgr)
return dp[node]
def sdd_exactly_one_among(manager, active_variables, background_variables):
if not all(x in background_variables for x in active_variables):
raise Exception(
"Invalid argument active variables %s, background_variables %s " %
(active_variables, background_variables))
result = sdd.sdd_manager_false(manager)
for positive_variable in active_variables:
cur_term = sdd.sdd_manager_true(manager)
for variable in background_variables:
if variable != positive_variable:
cur_lit = sdd.sdd_manager_literal(-variable, manager)
else:
cur_lit = sdd.sdd_manager_literal(variable, manager)
cur_term = sdd.sdd_conjoin(cur_term, cur_lit, manager)
sdd.sdd_save("t1.sdd", result)
sdd.sdd_save("t2.sdd", cur_term)
sdd.sdd_vtree_save("manager.vtree", sdd.sdd_manager_vtree(manager))
result = sdd.sdd_disjoin(result, cur_term, manager)
return result
def disjoin2(self, a, b):
assert a is not None
assert b is not None
return sdd.sdd_disjoin(a, b, self.__manager)
def GetLocalConstraintsForInternalClusters(self, file_prefix):
if_vtree_filename = "%s/%s_if_vtree.vtree" % (file_prefix, self.name)
if_sdd_filename_prefix = "%s/%s_if_sdd" % (file_prefix, self.name)
then_vtree_filename = "%s/%s_then_vtree.vtree" % (file_prefix,
self.name)
then_sdd_filename_prefix = "%s/%s_then_sdd" % (file_prefix, self.name)
ifs = []
thens = []
if_variable_mapping = {}
if_sdd_index = 0
if_sdd_index += 1
if_variable_mapping[
"c%s" %
self.name] = if_sdd_index # cluster indicator for current cluster
for external_edge in self.external_edges:
if_sdd_index += 1
if_variable_mapping[str(external_edge)] = if_sdd_index
then_variable_mapping = {}
# variables for the child clusters
then_sdd_index = 0
zdd_to_sdd_index = [None]
for child in self.children:
then_sdd_index += 1
then_variable_mapping["c%s" % child] = then_sdd_index
universe = self.sub_region_edges.keys()
GraphSet.set_universe(universe)
universe = GraphSet.universe()
for node_pair in universe:
correponding_sdd_indexes = []
for internal_edge in self.sub_region_edges[node_pair]:
then_sdd_index += 1
then_variable_mapping[str(internal_edge)] = then_sdd_index
correponding_sdd_indexes.append(then_sdd_index)
zdd_to_sdd_index.append(correponding_sdd_indexes)
if_vtree, then_vtree = sdd.sdd_vtree_new(if_sdd_index,
"right"), sdd.sdd_vtree_new(
then_sdd_index, "right")
if_manager, then_manager = sdd.sdd_manager_new(
if_vtree), sdd.sdd_manager_new(then_vtree)
sdd.sdd_manager_auto_gc_and_minimize_off(if_manager)
sdd.sdd_manager_auto_gc_and_minimize_off(then_manager)
sdd.sdd_vtree_free(if_vtree)
sdd.sdd_vtree_free(then_vtree)
#none of the external edges are used and cluster indicator is off
case_index = 0
case_one_if = sdd.util.sdd_negative_term(if_manager,
range(1, if_sdd_index + 1))
case_one_then = sdd.util.sdd_negative_term(
then_manager, range(1, then_sdd_index + 1))
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
case_one_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
case_one_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
#none of the external edges are used and cluster indicator is on
case_index += 1
case_two_if = sdd.util.sdd_exactly_one_among(
if_manager, [if_variable_mapping["c%s" % self.name]],
range(1, if_sdd_index + 1))
#***Non empty path in this region map
none_of_child = sdd.util.sdd_negative_term(
then_manager,
[then_variable_mapping["c%s" % child] for child in self.children])
paths = GraphSet()
child_names = self.children.keys()
for c1, c2 in itertools.combinations(child_names, 2):
paths = paths.union(GraphSet.paths(c1, c2))
simple_path_constraint = generate_sdd_from_graphset(
paths, then_manager, zdd_to_sdd_index)
case_one = sdd.sdd_conjoin(simple_path_constraint, none_of_child,
then_manager)
#***Empty path in the region map
exactly_one_chlid = sdd.util.sdd_exactly_one(
then_manager,
[then_variable_mapping["c%s" % child] for child in self.children])
empty_path_constraint = sdd.util.sdd_negative_term(
then_manager, sum(zdd_to_sdd_index[1:], []))
case_two = sdd.sdd_conjoin(empty_path_constraint, exactly_one_chlid,
then_manager)
case_two_then = sdd.sdd_disjoin(case_one, case_two, then_manager)
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
case_two_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
case_two_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
#Exactly one of the external edge is used and cluster_indicator is off
aggregated_cases = {}
for external_edge in self.external_edges:
aggregated_cases.setdefault(self.external_edges[external_edge],
[]).append(external_edge)
for entering_node in aggregated_cases:
case_index += 1
cur_case_if = sdd.util.sdd_exactly_one_among(
if_manager, [
if_variable_mapping[str(e)]
for e in aggregated_cases[entering_node]
], range(1, if_sdd_index + 1))
paths = GraphSet()
for child in self.children:
if child == entering_node:
continue
paths = paths.union(GraphSet.paths(entering_node, child))
cur_case_then = generate_sdd_from_graphset(paths, then_manager,
zdd_to_sdd_index)
cur_case_then = sdd.sdd_disjoin(
cur_case_then,
sdd.util.sdd_negative_term(then_manager, [
then_variable_mapping[str(e)] for e in self.internal_edges
]), then_manager)
#conjoin that all the child indicator is off
cur_case_then = sdd.sdd_conjoin(
cur_case_then,
sdd.util.sdd_negative_term(then_manager, [
then_variable_mapping["c%s" % child]
for child in self.children
]), then_manager)
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
cur_case_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
cur_case_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
#Exactly two of the external edge is used and cluster_indicator is off
aggregated_cases = {}
for (i, j) in itertools.combinations(self.external_edges.keys(), 2):
entering_points = (self.external_edges[i], self.external_edges[j])
entering_points = (max(entering_points), min(entering_points))
aggregated_cases.setdefault(entering_points, []).append((i, j))
for entering_points in aggregated_cases:
case_index += 1
entering_edges = aggregated_cases[entering_points]
cur_case_if = generate_exactly_two_from_tuples(
if_manager,
[(if_variable_mapping[str(e1)], if_variable_mapping[str(e2)])
for (e1, e2) in entering_edges], range(1, if_sdd_index + 1))
if entering_points[0] == entering_points[1]:
cur_case_then = sdd.util.sdd_negative_term(
then_manager, range(1, then_sdd_index + 1))
else:
paths = GraphSet.paths(entering_points[0], entering_points[1])
cur_case_then = generate_sdd_from_graphset(
paths, then_manager, zdd_to_sdd_index)
cur_case_then = sdd.sdd_conjoin(
cur_case_then,
sdd.util.sdd_negative_term(then_manager, [
then_variable_mapping["c%s" % child]
for child in self.children
]), then_manager)
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
cur_case_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
cur_case_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
sdd.sdd_vtree_save(if_vtree_filename,
sdd.sdd_manager_vtree(if_manager))
sdd.sdd_vtree_save(then_vtree_filename,
sdd.sdd_manager_vtree(then_manager))
sdd.sdd_manager_free(if_manager)
sdd.sdd_manager_free(then_manager)
constraint = {}
constraint["if_vtree"] = if_vtree_filename
constraint["if"] = ifs
constraint["if_variable_mapping"] = if_variable_mapping
constraint["then_vtree"] = then_vtree_filename
constraint["then"] = thens
constraint["then_variable_mapping"] = then_variable_mapping
return constraint
def GetLocalConstraintsForLeaveClusters(self, file_prefix):
if_vtree_filename = "%s/%s_if_vtree.vtree" % (file_prefix, self.name)
if_sdd_filename_prefix = "%s/%s_if_sdd" % (file_prefix, self.name)
then_vtree_filename = "%s/%s_then_vtree.vtree" % (file_prefix,
self.name)
then_sdd_filename_prefix = "%s/%s_then_sdd" % (file_prefix, self.name)
ifs = []
thens = []
if_variable_mapping = {}
if_sdd_index = 0
if_sdd_index += 1
if_variable_mapping[
"c%s" %
self.name] = if_sdd_index # cluster indicator for current cluster
for external_edge in self.external_edges:
if_sdd_index += 1
if_variable_mapping[str(external_edge)] = if_sdd_index
then_variable_mapping = {}
zdd_to_sdd_index = [None]
universe = []
node_pair_to_edges = {}
for internal_edge in self.internal_edges:
if (internal_edge.x, internal_edge.y) not in node_pair_to_edges:
universe.append((internal_edge.x, internal_edge.y))
node_pair_to_edges.setdefault((internal_edge.x, internal_edge.y),
[]).append(internal_edge)
GraphSet.set_universe(universe)
universe = GraphSet.universe()
then_sdd_index = 0
for node_pair in universe:
correponding_sdd_indexes = []
for internal_edge in node_pair_to_edges[node_pair]:
then_sdd_index += 1
then_variable_mapping[str(internal_edge)] = then_sdd_index
correponding_sdd_indexes.append(then_sdd_index)
zdd_to_sdd_index.append(correponding_sdd_indexes)
if_vtree, then_vtree = sdd.sdd_vtree_new(if_sdd_index,
"right"), sdd.sdd_vtree_new(
then_sdd_index, "right")
if_manager, then_manager = sdd.sdd_manager_new(
if_vtree), sdd.sdd_manager_new(then_vtree)
sdd.sdd_manager_auto_gc_and_minimize_off(if_manager)
sdd.sdd_manager_auto_gc_and_minimize_off(then_manager)
sdd.sdd_vtree_free(if_vtree)
sdd.sdd_vtree_free(then_vtree)
#none of the external edges are used and cluster indicator is off
case_index = 0
case_one_if = sdd.util.sdd_negative_term(if_manager,
range(1, if_sdd_index + 1))
case_one_then = sdd.util.sdd_negative_term(
then_manager, range(1, then_sdd_index + 1))
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
case_one_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
case_one_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
#none of the external edges are used and cluster indicator is on
case_index += 1
case_two_if = sdd.util.sdd_exactly_one_among(
if_manager, [if_variable_mapping["c%s" % self.name]],
range(1, if_sdd_index + 1))
paths = GraphSet()
for (i, j) in itertools.combinations(self.nodes, 2):
paths = paths.union(GraphSet.paths(i, j))
case_two_then = generate_sdd_from_graphset(paths, then_manager,
zdd_to_sdd_index)
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
case_two_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
case_two_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
#exactly one of the external edge is used and cluster indicator is off
aggregated_cases = {}
for external_edge in self.external_edges:
aggregated_cases.setdefault(self.external_edges[external_edge],
[]).append(external_edge)
for entering_node in aggregated_cases:
case_index += 1
cur_case_if = sdd.util.sdd_exactly_one_among(
if_manager, [
if_variable_mapping[str(e)]
for e in aggregated_cases[entering_node]
], range(1, if_sdd_index + 1))
paths = GraphSet()
for node in self.nodes:
if node == entering_node:
continue
paths = paths.union(GraphSet.paths(entering_node, node))
cur_case_then = generate_sdd_from_graphset(paths, then_manager,
zdd_to_sdd_index)
# disjoin the empty path
cur_case_then = sdd.sdd_disjoin(
cur_case_then,
sdd.util.sdd_negative_term(then_manager,
range(1, then_sdd_index + 1)),
then_manager)
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
cur_case_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
cur_case_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
# exactly two of the external edge is used and cluster_indicator is off
aggregated_cases = {}
for (i, j) in itertools.combinations(self.external_edges.keys(), 2):
entering_points = (self.external_edges[i], self.external_edges[j])
entering_points = (max(entering_points), min(entering_points))
aggregated_cases.setdefault(entering_points, []).append((i, j))
for entering_points in aggregated_cases:
case_index += 1
entering_edges = aggregated_cases[entering_points]
cur_case_if = generate_exactly_two_from_tuples(
if_manager,
[(if_variable_mapping[str(e1)], if_variable_mapping[str(e2)])
for (e1, e2) in entering_edges], range(1, if_sdd_index + 1))
if entering_points[0] == entering_points[1]:
cur_case_then = sdd.util.sdd_negative_term(
then_manager, range(1, then_sdd_index + 1))
else:
paths = GraphSet.paths(entering_points[0], entering_points[1])
cur_case_then = generate_sdd_from_graphset(
paths, then_manager, zdd_to_sdd_index)
sdd.sdd_save("%s_%s" % (if_sdd_filename_prefix, case_index),
cur_case_if)
sdd.sdd_save("%s_%s" % (then_sdd_filename_prefix, case_index),
cur_case_then)
ifs.append("%s_%s" % (if_sdd_filename_prefix, case_index))
thens.append("%s_%s" % (then_sdd_filename_prefix, case_index))
sdd.sdd_vtree_save(if_vtree_filename,
sdd.sdd_manager_vtree(if_manager))
sdd.sdd_vtree_save(then_vtree_filename,
sdd.sdd_manager_vtree(then_manager))
sdd.sdd_manager_free(if_manager)
sdd.sdd_manager_free(then_manager)
constraint = {}
constraint["if_vtree"] = if_vtree_filename
constraint["if"] = ifs
constraint["if_variable_mapping"] = if_variable_mapping
constraint["then_vtree"] = then_vtree_filename
constraint["then"] = thens
constraint["then_variable_mapping"] = then_variable_mapping
return constraint
def _encode_grid_aux(source,sink,nodes,graph,manager,
base=None,cache=None,verbose=False):
nodes = sorted(nodes)
key = (source,tuple(nodes))
if cache and key in cache:
return cache[key]
if True: # INITIALIZATION FOR (S,T) PATHS
if sink not in nodes: # unreachable
return sdd.sdd_manager_false(manager)
if len(nodes) == 1: # must be sink
return sdd.sdd_manager_true(manager)
if not g.reachable(source,sink,nodes):
alpha = sdd.sdd_manager_false(manager)
cache[key] = alpha
return alpha
if source == sink:
# turn off all other edges
alpha = sdd.sdd_manager_true(manager)
sdd.sdd_ref(alpha,manager)
my_nodes = list(nodes)
my_nodes.remove(source)
for node in my_nodes: # for all unused nodes
edges = graph.incident_edges(node,nodes=nodes)
sdd_vars = [ graph.edge_to_index[edge] + 1 for edge in edges ]
all_false = all_false_term(sdd_vars,manager)
alpha,tmp = sdd.sdd_conjoin(alpha,all_false,manager),alpha
sdd.sdd_ref(alpha,manager); sdd.sdd_deref(tmp,manager)
cache[key] = alpha
return alpha
alpha = sdd.sdd_manager_false(manager)
sdd.sdd_ref(alpha,manager)
else: # INITIALIZATION FOR ALL PATHS STARTING FROM S
# empty graph, source should equal sink
if len(nodes) == 1:
return sdd.sdd_manager_true(manager)
# initial case: no more paths
alpha = sdd.sdd_manager_true(manager)
sdd.sdd_ref(alpha,manager)
my_nodes = list(nodes)
my_nodes.remove(source)
for node in my_nodes: # for all unused nodes
edges = graph.incident_edges(node,nodes=nodes)
sdd_vars = [ graph.edge_to_index[edge] + 1 for edge in edges ]
all_false = all_false_term(sdd_vars,manager)
alpha,tmp = sdd.sdd_conjoin(alpha,all_false,manager),alpha
sdd.sdd_ref(alpha,manager); sdd.sdd_deref(tmp,manager)
# after this, try to extend the paths
# first, find incident edges
edges = graph.incident_edges(source,nodes=nodes)
sdd_vars = [ graph.edge_to_index[edge] + 1 for edge in edges ]
all_false = all_false_term(sdd_vars,manager)
sdd.sdd_ref(all_false,manager)
# for each incident edge
my_nodes = list(nodes)
my_nodes.remove(source)
for edge,sdd_var in zip(edges,sdd_vars):
# recurse
neighbor = Graph.neighbor(source,edge)
gamma = _encode_grid_aux(neighbor,sink,my_nodes,graph,manager,
base=base,cache=cache,verbose=verbose)
if sdd.sdd_node_is_false(gamma): continue
# exactly one edge on
sdd_lit = sdd.sdd_manager_literal(sdd_var,manager)
beta = sdd.sdd_exists(sdd_var,all_false,manager)
beta = sdd.sdd_conjoin(beta,sdd_lit,manager)
beta = sdd.sdd_conjoin(beta,gamma,manager)
# accumulate
alpha,tmp = sdd.sdd_disjoin(alpha,beta,manager),alpha
sdd.sdd_ref(alpha,manager); sdd.sdd_deref(tmp,manager)
sdd.sdd_deref(all_false,manager)
cache[key] = alpha
return alpha
def generate_sdd_from_graphset(paths, sdd_manager, zdd_edge_to_sdd_edges):
try:
zdd_file = tempfile.TemporaryFile()
paths.dump(zdd_file)
zdd_file.seek(0)
zdd_content = zdd_file.readlines()
finally:
zdd_file.close()
# handle the trivial logic
if zdd_content[0].strip() == "T":
result_sdd = sdd.sdd_manager_true(sdd_manager)
for sdd_edges in zdd_edge_to_sdd_edges:
cur_neg_term = sdd.util.sdd_negative_term(sdd_manager, sdd_edges)
result_sdd = sdd.sdd_conjoin(result_sdd, cur_neg_term, sdd_manager)
return result_sdd
if zdd_content[0].strip() == "B":
result_sdd = sdd.sdd_manager_false(sdd_manager)
return result_sdd
pos_zdd_indicator_to_sdd = [None]
neg_zdd_indicator_to_sdd = [None]
for sdd_edges in zdd_edge_to_sdd_edges:
if sdd_edges:
pos_zdd_indicator_to_sdd.append(
sdd.util.sdd_exactly_one(sdd_manager, sdd_edges))
neg_zdd_indicator_to_sdd.append(
sdd.util.sdd_negative_term(sdd_manager, sdd_edges))
conversion_map = {} # key is the node index and the value is a sdd node
decision_variable_map = {
} # key is the node index and the value is the variable index
last_node_index = None
zdd_variable_size = len(zdd_edge_to_sdd_edges) - 1
def complete_zdd_child(variable_index, child, conversion_map,
decision_variable_map, zdd_variable_size,
sdd_manager):
if child == "T":
if variable_index != zdd_variable_size:
skipped_variables = range(variable_index + 1,
zdd_variable_size + 1)
neg_terms = sdd.util.sdd_negative_term(
sdd_manager,
sum([zdd_edge_to_sdd_edges[x] for x in skipped_variables],
[]))
return neg_terms
else:
return sdd.sdd_manager_true(sdd_manager)
elif child == "B":
return sdd.sdd_manager_false(sdd_manager)
else:
child = int(child)
child_variable = decision_variable_map[child]
if child_variable == variable_index + 1:
return conversion_map[child]
else:
skipped_variables = range(variable_index + 1, child_variable)
neg_terms = sdd.util.sdd_negative_term(
sdd_manager,
sum([zdd_edge_to_sdd_edges[x] for x in skipped_variables],
[]))
return sdd.sdd_conjoin(neg_terms, conversion_map[child],
sdd_manager)
for line in zdd_content:
line = line.strip()
if line == ".":
break
line_toks = line.split(" ")
node_index = int(line_toks[0])
variable_index = int(line_toks[1])
low_child = line_toks[2]
high_child = line_toks[3]
sdd_low_child = None
sdd_high_child = None
sdd_low_child = complete_zdd_child(variable_index, low_child,
conversion_map,
decision_variable_map,
zdd_variable_size, sdd_manager)
sdd_high_child = complete_zdd_child(variable_index, high_child,
conversion_map,
decision_variable_map,
zdd_variable_size, sdd_manager)
cur_node_positive_element = sdd.sdd_conjoin(
pos_zdd_indicator_to_sdd[variable_index], sdd_high_child,
sdd_manager)
cur_node_negative_element = sdd.sdd_conjoin(
neg_zdd_indicator_to_sdd[variable_index], sdd_low_child,
sdd_manager)
conversion_map[node_index] = sdd.sdd_disjoin(
cur_node_negative_element, cur_node_positive_element, sdd_manager)
decision_variable_map[node_index] = variable_index
last_node_index = node_index
result = conversion_map[last_node_index]
if decision_variable_map[last_node_index] != 1:
skipped_variables = range(1, decision_variable_map[last_node_index])
neg_terms = sdd.util.sdd_negative_term(
sdd_manager,
sum([zdd_edge_to_sdd_edges[x] for x in skipped_variables], []))
result = sdd.sdd_conjoin(neg_terms, conversion_map[last_node_index],
sdd_manager)
return result
def str_model(model, var_count=None):
"""Convert model to string."""
if var_count is None:
var_count = len(model)
return " ".join(str(model[var]) for var in xrange(1, var_count + 1))
if __name__ == '__main__':
var_count = 10
vtree = sdd.sdd_vtree_new(var_count, "balanced")
manager = sdd.sdd_manager_new(vtree)
alpha = sdd.sdd_manager_false(manager)
for var in xrange(1, var_count + 1):
lit = sdd.sdd_manager_literal(-var, manager)
alpha = sdd.sdd_disjoin(alpha, lit, manager)
vt = sdd.sdd_manager_vtree(manager)
model_count = 0
for model in models(alpha, vt):
model_count += 1
print str_model(model, var_count=var_count)
#lib_mc = sdd.sdd_model_count(alpha,manager)
print "model count: %d" % model_count
sdd.sdd_manager_free(manager)
sdd.sdd_vtree_free(vtree)
def parse_bdd(filename,var_count=None):
if var_count is None:
var_count,node_count = pre_parse_bdd(filename)
else:
max_count,node_count = pre_parse_bdd(filename)
#print " zdd var count:", var_count
#print " zdd node count:", node_count
manager = start_manager(var_count,range(1,var_count+1))
root = sdd.sdd_manager_vtree(manager)
nodes = [None] * (node_count+1)
index,id2index = 1,{}
f = open(filename)
for line in f.readlines():
if line.startswith("."): break
line = line.strip().split()
nid = int(line[0])
dvar = int(line[1])
lo,hi = line[2],line[3]
hi_lit = sdd.sdd_manager_literal( dvar,manager)
lo_lit = sdd.sdd_manager_literal(-dvar,manager)
if lo == 'T':
lo_sdd,lo_vtree = sdd.sdd_manager_true(manager),None
elif lo == 'B':
lo_sdd,lo_vtree = sdd.sdd_manager_false(manager),None
else:
lo_id = int(lo)
lo_sdd,lo_vtree = nodes[id2index[lo_id]]
if hi == 'T':
hi_sdd,hi_vtree = sdd.sdd_manager_true(manager),None
elif hi == 'B':
hi_sdd,hi_vtree = sdd.sdd_manager_false(manager),None
else:
hi_id = int(hi)
hi_sdd,hi_vtree = nodes[id2index[hi_id]]
#v1,v2 = sdd.sdd_vtree_of(hi_lit),sdd.sdd_vtree_of(hi_sdd)
#vt = sdd.sdd_vtree_lca(v1,v2,root)
vt = sdd.sdd_manager_vtree_of_var(dvar,manager)
vt = sdd.sdd_vtree_parent(vt)
vt = sdd.sdd_vtree_right(vt)
if dvar < var_count:
hi_sdd = zero_normalize_sdd(hi_sdd,hi_vtree,vt,manager)
lo_sdd = zero_normalize_sdd(lo_sdd,lo_vtree,vt,manager)
vt = sdd.sdd_vtree_parent(vt)
hi_sdd = sdd.sdd_conjoin(hi_lit,hi_sdd,manager)
lo_sdd = sdd.sdd_conjoin(lo_lit,lo_sdd,manager)
alpha = sdd.sdd_disjoin(hi_sdd,lo_sdd,manager)
nodes[index] = (alpha,vt)
id2index[nid] = index
index += 1
f.close()
last_sdd,last_vtree = nodes[-1]
vt = sdd.sdd_manager_vtree(manager)
if vt != last_vtree:
last_sdd = zero_normalize_sdd(last_sdd,last_vtree,vt,manager)
return manager,last_sdd
def disjoin2(self, a, b):
return sdd.sdd_disjoin(a, b, self.__manager)
def compile_all(forest_sdds,
used_vars_list,
num_trees,
domain,
manager,
constraint_sdd=None):
half = int(math.ceil(num_trees / 2.0))
true_sdd = sdd.sdd_manager_true(manager)
false_sdd = sdd.sdd_manager_false(manager)
last_size = 2**16
if not constraint_sdd:
constraint_sdd = sdd.sdd_manager_true(manager)
true_sdd = constraint_sdd
sdd.sdd_ref(true_sdd, manager)
to_compile_sdds = [tree_sdd for tree_sdd in forest_sdds]
used_vars_list = [used_vars for used_vars in used_vars_list]
'''
if OPTIONS.majority_circuit_opt:
majority_sdds = [sdd.sdd_manager_literal(domain["Tree_%d" % i], manager) for i in xrange(num_trees)]
for single_sdd in majority_sdds:
sdd.sdd_ref(single_sdd, manager)
to_compile_sdds = majority_sdds
used_vars_list = [set() for _ in forest_sdds]
'''
cur = [true_sdd, false_sdd]
used_vars = set()
for k in xrange(num_trees):
last, cur = cur, []
tree_index = pick_next_tree(used_vars_list, used_vars)
tree_sdd = to_compile_sdds[tree_index]
used_vars |= used_vars_list[tree_index]
to_compile_sdds = to_compile_sdds[:tree_index] + to_compile_sdds[
tree_index + 1:]
used_vars_list = used_vars_list[:tree_index] + used_vars_list[
tree_index + 1:]
for i in xrange(min(half, k + 1) + 1):
cur_sdd = last[i]
#cur_sdd = sdd.sdd_conjoin(sdd.sdd_negate(tree_sdd,manager),cur_sdd,manager)
"""
elif i+(num_trees-k) < half: # don't bother
cur_sdd = sdd.sdd_manager_false(manager)
"""
if i == 0:
pass
elif i > 0:
alpha = sdd.sdd_conjoin(tree_sdd, last[i - 1], manager)
sdd.sdd_deref(last[i - 1], manager)
cur_sdd = sdd.sdd_disjoin(cur_sdd, alpha, manager)
sdd.sdd_ref(cur_sdd, manager)
cur.append(cur_sdd)
if sdd.sdd_manager_dead_count(manager) >= 2 * last_size:
sdd.sdd_manager_garbage_collect(manager)
if sdd.sdd_manager_live_count(manager) >= 2 * last_size:
print "*",
sdd.sdd_manager_minimize_limited(manager)
last_size = 2 * last_size
if k >= half: sdd.sdd_deref(last[-2], manager)
sdd.sdd_deref(tree_sdd, manager)
cur.append(false_sdd)
print "%d" % (num_trees - k),
sys.stdout.flush()
#print "%d/%d" % (k,num_trees)
print "live size:", sdd.sdd_manager_live_count(manager)
#print "dead size:", sdd.sdd_manager_dead_count(manager)
sdd.sdd_manager_garbage_collect(manager)
#sdd.sdd_manager_minimize_limited(manager)
#for alpha in cur: sdd.sdd_deref(alpha,manager)
ret = cur[-2]
'''
if OPTIONS.majority_circuit_opt:
# save ret (the majority circuit)
# save each individual tree_sdd
vtree = sdd.sdd_manager_vtree(manager)
majority_sdd_filename = "%s_majority.sdd" % sdd_basename
majority_vtree_filename = "%s_majority.vtree" % sdd_basename
print "Writing majority sdd file %s and majority vtree file %s" % (majority_sdd_filename, majority_vtree_filename)
sdd.sdd_save(majority_sdd_filename,ret)
sdd.sdd_vtree_save(majority_vtree_filename,vtree)
print "Writing individual tree sdds..."
for k,tree_sdd in enumerate(forest_sdds):
tree_name = "tree_%d" % k
tree_sdd_filename = "%s_majority_%s.sdd" % (sdd_basename, tree_name)
sdd.sdd_save(tree_sdd_filename, tree_sdd)
gamma = sdd.sdd_manager_true(manager)
for k,tree_sdd in enumerate(forest_sdds):
new_gamma = sdd.sdd_conjoin(gamma, tree_sdd, manager)
sdd.sdd_ref(new_gamma, manager)
sdd.sdd_deref(gamma, manager)
gamma = new_gamma
if sdd.sdd_manager_dead_count(manager) >= 2*last_size:
sdd.sdd_manager_garbage_collect(manager)
if sdd.sdd_manager_live_count(manager) >= 2*last_size:
print "*",
sdd.sdd_manager_minimize_limited(manager)
last_size = 2*last_size
print "%d" % k,
sys.stdout.flush()
print "live size:", sdd.sdd_manager_live_count(manager)
ret = sdd.sdd_conjoin(ret, gamma, manager)
#existential quantification
print "Existential quantification..."
exists_map = sdd.new_intArray(len(domain))
for i in xrange(len(domain)):
sdd.intArray_setitem(exists_map,i,0)
for i in xrange(num_trees):
lit = domain["Tree_%d" % i]
sdd.intArray_setitem(exists_map,lit,1)
ret = sdd.sdd_exists_multiple(exists_map, ret, manager)
'''
return ret
def sdd_disjunctive_of_terms(manager, variables, positive_variable_tuples):
result = sdd.sdd_manager_false(manager)
for positive_tuple in positive_variable_tuples:
cur_term = sdd_term(manager, variables, positive_tuple)
result = sdd.sdd_disjoin(result, cur_term, manager)
return result
def str_model(model, var_count=None):
"""Convert model to string."""
if var_count is None:
var_count = len(model)
return " ".join(str(model[var]) for var in xrange(1, var_count + 1))
if __name__ == "__main__":
var_count = 10
vtree = sdd.sdd_vtree_new(var_count, "balanced")
manager = sdd.sdd_manager_new(vtree)
alpha = sdd.sdd_manager_false(manager)
for var in xrange(1, var_count + 1):
lit = sdd.sdd_manager_literal(-var, manager)
alpha = sdd.sdd_disjoin(alpha, lit, manager)
vt = sdd.sdd_manager_vtree(manager)
model_count = 0
for model in models(alpha, vt):
model_count += 1
print str_model(model, var_count=var_count)
# lib_mc = sdd.sdd_model_count(alpha,manager)
print "model count: %d" % model_count
sdd.sdd_manager_free(manager)
sdd.sdd_vtree_free(vtree)